Frommeyer, G.; Knippscheer, S.; Rablbauer, R.: Struktur und Eigenschaften von Titanaluminiden (TiAl) - Leichtbaulegierungen für High Performance Motorkomponenten. Clauthal Industriekolloquium Sonderforschungsbereich 675, Clausthal (2007)
Frommeyer, G.; Rablbauer, R.; Brokmeier, K.: Entwicklung und Eigenschaften ultrahochfester und supraduktiler Stähle für den Fahrzeugbau. Clausthal Industriekolloquium Sonderforschungsbereich 675, Clausthal (2007)
Rablbauer, R.; Dönecke, K.; Hassel, A. W.; Frommeyer, G.: Mechanical Properties and Corrosion Behaviour of Ferritic Stainless Al Cr Steels. EUROMAT 2007, European Congress and Exhibition an Advanced Materials and Processes, Nürnberg, Germany (2007)
Hassel, A. W.; Lill, K. A.; Rablbauer, R.; Stratmann, M.: Corrosion and passivity of FeAlCr light weight steels. 58th Annual Meeting of the International Society of Electrochemistry, Banff, Canada (2007)
Frommeyer, G.; Rablbauer, R.; Fischer, R.: Properties of refractory NiAl(Cr, Mo, Re) alloys in relation to atomic defects and microstructures. TMS 2007 Annual Meeting, Orlando, FL, USA (2007)
Frommeyer, G.; Rablbauer, R.: Properties of refractory NiAl-(Cr, Mo, Re) alloys in relation to Atomic Defects and Microstructures. High Temperature Materials Chemistry, Wien, Austria (2006)
Rablbauer, R.: Mikrostrukturen und Eigenschaften quasibinärer eutektischer NiAl-Re und NiAl-(Ti,Zr,Hf)B2-Legierungen für den Hochtemperatureinsatz. Dissertation, RWTH Aachen, Aachen, Germany (2006)
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.